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Binary Image Steganalysis Based on Distortion Level Co-Occurrence Matrix

Computers, Materials & Continua 2018年第5期55卷 201-211页

作者： Junjia Chen Wei Lu yuileong yeung Yingjie Xue Xianjin Liu Cong Lin Yue Zhang School of Data and Computer Science Guangdong Key Laboratory of Information Security TechnologySun Yat-sen UniversityGuangzhou 510006China State Key Laboratory of Information Security Institute of Information EngineeringChinese Academy of SciencesBeijing 100093China Center for Faculty Development and Educational Technology Guangdong University of Finance and EconomicsGuangzhou 510320China Department of Computer Science College of Engineering and Computer ScienceEastern Lake AvenueOrlandoFLUSA.

In recent years,binary image steganography has developed so rapidly that the research of binary image steganalysis becomes more important for information *** most state-of-the-art binary image steganographic schemes,they always find out the flippable pixels to minimize the embedding *** this reason,the stego images generated by the previous schemes maintain visual quality and it is hard for steganalyzer to capture the embedding trace in spacial ***,the distortion maps can be calculated for cover and stego images and the difference between them is *** this paper,a novel binary image steganalytic scheme is proposed,which is based on distortion level co-occurrence *** proposed scheme first generates the corresponding distortion maps for cover and stego *** the co-occurrence matrix is constructed on the distortion level maps to represent the features of cover and stego ***,support vector machine,based on the gaussian kernel,is used to classify the *** with the prior steganalytic methods,experimental results demonstrate that the proposed scheme can effectively detect stego images.

关键词： Binary image steganalysis informational security embedding distortion distortion level map co-occurrence matrix support vector machine.

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